Modify Columns - Practice Coding Problems

Modify Columns - Problem

Databse Easy

You have a DataFrame employees with two columns:

Column Name	Type
name	object
salary	int

A company intends to give its employees a pay rise. Write a solution to modify the salary column by multiplying each salary by 2.

The result should be the modified DataFrame with updated salaries.

Input & Output

Example 1 — Basic Employee DataFrame

$ Input: employees = [{"name": "Alice", "salary": 50000}, {"name": "Bob", "salary": 60000}]

› Output: [{"name": "Alice", "salary": 100000}, {"name": "Bob", "salary": 120000}]

💡 Note: Alice's salary: 50000 × 2 = 100000, Bob's salary: 60000 × 2 = 120000

Example 2 — Single Employee

$ Input: employees = [{"name": "John", "salary": 75000}]

› Output: [{"name": "John", "salary": 150000}]

💡 Note: John's salary doubled: 75000 × 2 = 150000

Example 3 — Multiple Employees

$ Input: employees = [{"name": "Emma", "salary": 40000}, {"name": "Mike", "salary": 80000}, {"name": "Sara", "salary": 55000}]

› Output: [{"name": "Emma", "salary": 80000}, {"name": "Mike", "salary": 160000}, {"name": "Sara", "salary": 110000}]

💡 Note: All salaries doubled: Emma 40000→80000, Mike 80000→160000, Sara 55000→110000

Constraints

1 ≤ employees.length ≤ 10⁴
1 ≤ salary ≤ 10⁶
name consists of alphanumeric characters and spaces

Visualization

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Understanding the Visualization

Input DataFrame

Original employee data with name and salary columns

Salary Multiplication

Apply × 2 operation to entire salary column

Updated DataFrame

Modified DataFrame with doubled salaries

Key Takeaway

🎯 Key Insight: Use vectorized DataFrame operations to efficiently modify entire columns at once rather than processing rows individually

Asked in

G Google 15 a Amazon 12 M Microsoft 10 f Facebook 8

The key insight is to use vectorized DataFrame operations to modify entire columns at once. The optimal approach uses employees['salary'] = employees['salary'] * 2 for efficient bulk operations. Time: O(n), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ Vectorized Column Operation	O(n)	O(1)	Apply multiplication to entire salary column at once
Row-by-Row Modification	O(n)	O(1)	Iterate through each row and multiply salary by 2

Vectorized Column Operation — Algorithm Steps

Access the salary column directly
Apply multiplication operation to entire column
Result is automatically updated in DataFrame

Visualization

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Step-by-Step Walkthrough

Input DataFrame

Original employee data

Column Operation

Multiply entire salary column by 2

Updated DataFrame

All salaries doubled instantly

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

typedef struct {
    char name[100];
    int salary;
} Employee;

void solution(Employee* employees, int size) {
    for (int i = 0; i < size; i++) {
        employees[i].salary *= 2;
    }
}

int main() {
    char input[1000];
    fgets(input, sizeof(input), stdin);
    Employee employees[100];
    int size = 1;
    strcpy(employees[0].name, "John");
    employees[0].salary = 1000;
    
    solution(employees, size);
    
    printf("[{\"name\":\"%s\",\"salary\":%d}]\n", employees[0].name, employees[0].salary);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Single vectorized operation processes all n salary values

✓ Linear Growth

Space Complexity

O(1)

Modifying DataFrame in-place, no additional space needed

✓ Linear Space

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Vectorized Column Operation — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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